Principal Machine Learning Engineer, Recommendation Systems

OverviewPrincipal Machine Learning Engineer, Recommendation Systems — Launch PotatoJoin to apply for the Principal Machine Learning Engineer, Recommendation Systems role at Launch PotatoLaunch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState.
As The Discovery and Conversion Company, our mission is to connect consumers with the world's leading brands through data-driven content and technology.
Headquartered in South Florida with a remote-first team spanning over 15 countries, we've built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.
Must Have
Expertise building ML systems with deep expertise in large-scale personalization
Recognized industry expertise through patents, publications, or significant product impact
Proven success architecting ML platforms serving billions of predictions in production
Demonstrated track record of 0?1 innovation in personalization or recommender systems
Mastery across multiple ML domains including deep learning, causal inference, multi-armed bandits, and graph-based models
Experience
10+ years designing, developing, and deploying large-scale machine learning systems with a focus on personalization
Your Role
Establish the technical vision for personalization at Launch Potato, solving the company's most complex ML challenges and influencing strategy, architecture, and innovation across teams.
Outcomes
Define company-wide personalization strategy and architecture, driving alignment across all ML teams
Solve critical technical challenges such as cold start, real-time learning, and exploration/exploitation tradeoffs
Design and implement advanced ML solutions using cutting-edge techniques (e.g., graph neural networks, causal models, bandit algorithms)
Create and enforce ML architecture patterns, design standards, and reusable infrastructure across teams
Lead multi-quarter, cross-functional initiatives that redefine how personalization impacts business KPIs
Act as technical mentor to senior ML engineers, guiding complex decision-making and scaling team capability
Represent Launch Potato's technical brand externally through speaking engagements, open source contributions, or publications
Champion privacy-preserving personalization, responsible AI practices, and adaptive learning systems
Competencies
Visionary Thinking: Defines the future state of ML infrastructure and personalization strategy.
Balances deep technical rigor with a strong understanding of product impact.
Architectural Excellence: Designs scalable, modular systems that support billions of predictions and enable rapid experimentation.
Sets high standards for maintainability and performance.
Technical Influence: Drives decision-making and builds consensus across teams and stakeholders without direct authority.
Provides trusted guidance in ambiguous situations.
Expert-Level Execution: Navigates deep technical complexity while maintaining execution velocity.
Translates research insights into production-ready solutions.
Mentorship & Leadership: Coaches senior engineers, facilitates technical reviews, and raises the technical bar for the entire organization.
External Thought Leadership: Represents LP in the ML community and contributes to growing its reputation as a leader in ML innovation.
Curious & Forward-Looking: Constantly explores new approaches to personalization and actively prototypes cutting-edge methodologies.
Want to accelerate your career?
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Since day one, we\'ve been committed to having a diverse, inclusive team and culture.
We are proud to be an Equal Employment Opportunity company.
We value diversity, equity, and inclusion.
We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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